ABSTRACT Upper airway surgery encompasses a group of procedures commonly used to treat upper airway obstruction, including maxillomandibular advancement, surgery of the soft palate, nasal surgery, tongue reduction surgery, and correction of tracheal stenosis. Current diagnosis and the subsequent decision-making of these pathologies primarily rely on the clinical examination and objective measures such as acoustic rhinometry and rhinomanometry that do not correlate well with patient symptoms. The lack of dependable objective measures has resulted in improper procedural prescriptions and less accurate surgical corrections. In our Phase I project, we developed a virtual surgical planning system that incorporates computational fluid dynamics (CFD) simulations to address the clinical need for objective, reproducible and personalized surgical procedures. The Phase I project was executed with combined expertise in software development, biomechanical modeling of nasal airway passages, mathematical modeling of fluid flows and upper airway surgical treatment from the Medical College of Wisconsin (MCW), University of North Carolina (UNC), and Kitware. The biophysical metrics computed from CFD models correlated well with subjective measures of symptoms before and after surgery. The GPU-based implementation of our Lattice Boltzmann flow simulation provided a continuous feedback and furnished rapid updates of the flow field and metrics engendered by each virtual surgery. The Phase I proof-of-concept study has successfully achieved its aims and provided a solid understanding of the challenges and opportunities in clinical deployment of virtual surgical planning. In this Phase II project, we will 1) Extend and refine the virtual surgery and airflow simulation technology developed in Phase I, 2) Build a web-based application to deploy our patient-specific, geometrical and simulation-based surgical planning system in a cloud-based infrastructure, and 3) Conduct a validation study to evaluate the impact of virtual surgery modeling on surgeon decision-making for upper airway surgical planning. At the successful completion of these aims, we will have completed the groundwork needed to launch the commercialization effort. In summary, the innovation in this proposal lies in the unique strategy to build a continuous-feedback, patient-specific, geometrical and air flow simulation-based surgical planning system. The significance of this proposal lies in that the proposed surgical modeling system will be a powerful tool to provide surgeons with reliable, patient-specific objective measures to improve patient outcomes.